Field of the Invention
This invention relates to management and viewing of medical images and, more particularly, to systems and methods of comparing related medical images in order to detect differences in the compared images.
Description of the Related Art
Medical imaging is increasingly moving into the digital realm. This includes imaging techniques that were traditionally analog, such as mammography, x-ray imaging, angiography, endoscopy, and pathology, where information can now be acquired directly using digital sensors, or by digitizing information that was acquired in analog form. In addition, many imaging modalities are inherently digital, such as MRI, CT, nuclear medicine, and ultrasound. Increasingly these digital images are viewed, manipulated, and interpreted using computers and related computer equipment. Accordingly, there is a need for improved systems and methods of viewing and manipulating these digital images.
When comparison of related images is required, subtle differences between images may be difficult to detect. For example, if a lung radiograph from two months previous, and a current lung radiograph are to be compared in order to determine if any changes have occurred in the lungs over the previous two months, the viewer or reader typically views the two x-rays side by side. For example, the viewer or reader may have two monitors placed side by side, wherein each of the monitors displays a chest radiographic image. Alternatively, the viewer may view the two images side by side on a single monitor. However, as those of skill in the art will recognize, identifying differences in related images in this manner is often tedious and difficult. Some imaging modalities, such as CT and MRI, produce a large number of images, hundreds to even thousands of images per exam. In many cases, comparison of different series of images within the exam is required. For example, comparison of pre and post contrast images to detect areas of enhancement or comparison of PET and CT images for localization of activity is often necessary. Further, these often large exams may need to be compared to multiple prior exams to detect subtle, progressive changes over time, for example to detect a small, growing tumor. Current imaging software does not provide a satisfactory method for comparing images contained in two or more image series. Accordingly, systems and methods for comparison of images of multiple image series so that differences in the images may be more easily distinguishable are desired.